21 citations · 33 across the 5 of their papers we have counts for
5 papers
Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design
Latent Labs Team, Sebastian M. Schmon, Daniella Pretorius +17
Drug discovery relies on iterative expert workflows that are slow to parallelize and difficult to scale. Here we introduce Latent-Y, an AI agent that autonomously executes complete…
Latent-X: An Atom-level Frontier Model for De Novo Protein Binder Design
Latent Labs Team, Alex Bridgland, Jonathan Crabbé +13
Traditional drug discovery relies on rounds of screening millions of candidate molecules with low success rates, making drug discovery time and resource intensive. To overcome this…
ABodyBuilder3: Improved and scalable antibody structure predictions
Henry Kenlay, Frédéric A. Dreyer, Daniel Cutting +2
Accurate prediction of antibody structure is a central task in the design and development of monoclonal antibodies, notably to understand both their developability and their bindin…
Large scale paired antibody language models
Henry Kenlay, Frédéric A. Dreyer, Aleksandr Kovaltsuk +3
Antibodies are proteins produced by the immune system that can identify and neutralise a wide variety of antigens with high specificity and affinity, and constitute the most succes…
Inverse folding for antibody sequence design using deep learning
Frédéric A. Dreyer, Daniel Cutting, Constantin Schneider +2
We consider the problem of antibody sequence design given 3D structural information. Building on previous work, we propose a fine-tuned inverse folding model that is specifically o…